I did this the other day, but the changeover to the new software slowed me down. I’ve gathered a list of hitters along with their 2004 SSPS predicted and actual averages. I present the top 25 overachievers (actual average exceeding the predicted average) and top-25 underachievers (predicted average exceeds actual average). I was trying to find some underlying cause of the “Ichiro problem” so I list some of the factors, along with their Z-scores, that I think may be associated with the mis-predictions. The factors are the AVG-to-OBP ratio and speed (I use the average of 5 speed scores presented here). I also wanted to see how the 2005 prediction changed in response to the 2004 performance, which I call “bounce back.” So what are the trends? Let’s look at the overachievers first.

Top-25 Overachievers

Rank

Name

Residual

2004 AVG

2004 Pred

2005 Pred

Bounce Back

AVG/OBP

Z-Score of AVG/OBP

Speed Score

Z-Score of Speed Score

1

Ichiro Suzuki

0.0866

0.372

0.286

0.292

0.007

0.898

1.715

6.130

1.121

2

Adrian Beltre

0.0671

0.334

0.267

0.301

0.033

0.862

1.112

3.331

-0.575

3

Melvin Mora

0.0635

0.340

0.277

0.282

0.005

0.811

0.273

4.294

0.008

4

Ivan Rodriguez

0.0614

0.334

0.273

0.275

0.002

0.873

1.298

3.455

-0.500

5

Carlos Guillen

0.0425

0.318

0.275

0.280

0.005

0.838

0.723

6.770

1.509

6

Sean Casey

0.0407

0.324

0.283

0.301

0.018

0.851

0.933

3.724

-0.337

7

Mark Loretta

0.0391

0.335

0.296

0.310

0.013

0.858

1.044

4.342

0.038

8

Carlos Lee

0.0373

0.305

0.267

0.272

0.005

0.832

0.609

4.397

0.071

9

Javy Lopez

0.0353

0.316

0.281

0.271

-0.009

0.854

0.991

2.566

-1.039

10

Jack Wilson

0.0331

0.308

0.275

0.287

0.012

0.919

2.075

5.903

0.984

11

Juan Pierre

0.0319

0.326

0.294

0.301

0.007

0.872

1.283

7.382

1.880

12

Barry Bonds

0.0317

0.362

0.330

0.356

0.026

0.594

-3.351

4.797

0.314

13

Vladimir Guerrero

0.0307

0.337

0.306

0.301

-0.005

0.860

1.091

4.761

0.291

14

Jason Kendall

0.0290

0.319

0.290

0.294

0.005

0.799

0.075

4.053

-0.138

15

Lance Berkman

0.0290

0.316

0.287

0.302

0.015

0.703

-1.534

4.117

-0.099

16

Mike Young

0.0270

0.313

0.286

0.293

0.007

0.886

1.523

6.351

1.255

17

Scott Rolen

0.0265

0.314

0.288

0.300

0.013

0.768

-0.448

4.951

0.407

18

Miguel Tejada

0.0263

0.311

0.285

0.287

0.002

0.864

1.142

3.274

-0.609

19

Craig Monroe

0.0259

0.293

0.267

0.275

0.007

0.870

1.252

4.144

-0.083

20

Erubiel Durazo

0.0238

0.321

0.297

0.296

-0.001

0.810

0.251

3.655

-0.379

21

Carl Crawford

0.0232

0.296

0.272

0.282

0.010

0.893

1.638

10.719

3.902

22

Mark Kotsay

0.0232

0.314

0.290

0.303

0.012

0.848

0.882

4.540

0.158

23

Jim Edmonds

0.0224

0.301

0.279

0.288

0.009

0.720

-1.249

5.193

0.553

24

Raul Ibanez

0.0209

0.304

0.283

0.281

-0.002

0.860

1.079

2.924

-0.822

25

Cesar Izturis

0.0199

0.288

0.268

0.283

0.015

0.874

1.316

6.998

1.647

The most obvious similarity among these players is for AVG/OBP, which is something many people have noticed. While Bonds, Berkman, and Edmonds made the list, most of the guys are high AVG/OBP hitters. Interestingly enough, when I threw this variable into some regressions it did not have any impact on the prediction. I thought speed might matter, because speedy baserunners might be able to get on base on balls in play that would lead to outs for most players, but there does not seem to be much of a trend with this. Now, let’s look at the underachievers.

Top-25 Underachievers

Rank

Name

Residual

2004 AVG

2004 Pred

2005 Pred

Bounce Back

AVG/OBP

Z-Score of AVG/OBP

Speed Score

Z-Score of Speed Score

1

Scott Spiezio

-0.0664

0.215

0.282

0.270

-0.012

0.747

-0.799

4.546

0.161

2

Jason Phillips

-0.0609

0.218

0.279

0.275

-0.004

0.733

-1.027

1.848

-1.474

3

Desi Relaford

-0.0589

0.221

0.280

0.275

-0.005

0.747

-0.794

3.550

-0.443

4

Chipper Jones

-0.0461

0.248

0.294

0.289

-0.005

0.686

-1.823

2.486

-1.087

5

Alex Gonzalez

-0.0396

0.232

0.271

0.269

-0.002

0.858

1.047

3.609

-0.406

6

Jody Gerut

-0.0386

0.252

0.290

0.288

-0.002

0.753

-0.695

5.917

0.992

7

Jay Payton

-0.0366

0.260

0.296

0.293

-0.003

0.797

0.028

4.098

-0.110

8

Jose Valentin

-0.0333

0.216

0.249

0.234

-0.015

0.751

-0.739

5.687

0.853

9

Scott Podsednik

-0.0321

0.244

0.276

0.273

-0.003

0.779

-0.272

7.987

2.247

10

Alex Cintron

-0.0319

0.262

0.294

0.283

-0.011

0.871

1.272

4.562

0.171

11

Jose Cruz

-0.0317

0.242

0.274

0.269

-0.005

0.728

-1.121

6.239

1.187

12

Luis Gonzalez

-0.0304

0.259

0.289

0.286

-0.003

0.694

-1.681

4.673

0.238

13

Eric Chavez

-0.0282

0.276

0.304

0.306

0.002

0.695

-1.668

2.063

-1.344

14

Bret Boone

-0.0279

0.251

0.279

0.264

-0.015

0.792

-0.042

3.101

-0.715

15

Toby Hall

-0.0257

0.255

0.281

0.277

-0.004

0.850

0.914

0.762

-2.132

16

Joe Crede

-0.0253

0.239

0.264

0.259

-0.005

0.799

0.073

2.635

-0.997

17

Bernie Williams

-0.0253

0.262

0.287

0.282

-0.005

0.728

-1.119

2.355

-1.167

18

Corey Koskie

-0.0251

0.251

0.276

0.272

-0.004

0.734

-1.017

5.231

0.577

19

Mike Cameron

-0.0249

0.231

0.256

0.258

0.002

0.725

-1.171

5.766

0.900

20

Bobby Higginson

-0.0242

0.246

0.270

0.268

-0.002

0.695

-1.673

4.021

-0.157

21

Eric Hinske

-0.0222

0.246

0.268

0.269

0.002

0.786

-0.142

4.216

-0.039

22

Angel Berroa

-0.0221

0.262

0.284

0.276

-0.007

0.850

0.920

6.445

1.312

23

A.J. Pierzynski

-0.0221

0.272

0.294

0.303

0.010

0.852

0.953

1.232

-1.847

24

Vinny Castilla

-0.0219

0.271

0.293

0.301

0.008

0.817

0.364

2.207

-1.256

25

Carlos Pena

-0.0218

0.241

0.263

0.263

0.000

0.713

-1.362

5.317

0.628

There are a lot of guys here with lower AVG/OBPs, but the trend is not as strong as it was for the overachievers. Speed doesn’t seem to be much of a factor here, either. The good news for the system is that in 2005 the projections seem to be moving in the opposite directions.

Overall, I’m pretty pleased with the system. Some guys are hard to predict and may have combinations of unique skills that are difficult to quantify. I’m fine dealing with that. The next step is to move on to minor league predictions. I’ll let you know when I’m done.

Thursday, April 7th, 2005,
by JC and is filed under "General ".
Both comments and pings are currently closed.

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2 Responses “Where SSPS Goes Wrong with AVG”

Some of these guys, I definitely would have thought would be on these lists. Also, I wonder if Depodesta is working with something similar, picking up Phillips and Valentin. If Vinny Castilla hits .301 you deserve the nobel prize in Saberocity.

I do think that Vinny is a bit under-rated, but I think .301 is high. In SSPS Version 1, I assume that every player plays for the the same team as the previous year, so the Coors inflation is included in that. However, I would not be surprised if he his over .290. In the future, I hope to update projections for the correct team.